Towards hybrid statistical-deterministic wireless channel modelling of multiroom environments

The fluctuation of wireless signals propagating through a linear chain of cavities deviates from Gaussian. In multiply-connected environments, fluctuation statistics can be computed only in the room hosting the receiving terminal and can be used to establish fading margins independently from deterministic simulations performed for power coverage predictions. If the room hosting the detector is complex enough to support wave chaos and coupling with neighboring rooms is strong, those margins stand on the assumption of having Gaussian random signals. The signal fading induced at the receiving antenna critically depend on topology of and strength of coupling across the multiply connected environment. A simple formula for the kurtosis index of antenna currents that captures number of rooms and average number of channels coupling two contiguous rooms is obtained through the impedance-based random coupling model, which can be used to assist the fusion between deterministic and statistical coverage prediction tools.

[1]  Gregor Tanner,et al.  High frequency propagation in large and multiply connected electromagnetic environments , 2016, 2016 IEEE Metrology for Aerospace (MetroAeroSpace).

[2]  E. Ott,et al.  Random coupling model for wireless communication channels , 2014, 2014 International Symposium on Electromagnetic Compatibility.

[3]  Shen Lin,et al.  A Novel Statistical Model for the Electromagnetic Coupling to Electronics inside Enclosures , 2019, 2019 IEEE International Symposium on Electromagnetic Compatibility, Signal & Power Integrity (EMC+SIPI).

[4]  David A. Hill,et al.  Electromagnetic fields in cavities: Deterministic and statistical theories [Advertisement] , 2009 .

[5]  D. Hill,et al.  On the Use of Reverberation Chambers to Simulate a Rician Radio Environment for the Testing of Wireless Devices , 2006, IEEE Transactions on Antennas and Propagation.

[6]  Stefano Giani,et al.  Acoustic energy distributions in multi-component structures - dynamical energy analysis versus numerically exact results , 2010 .

[7]  Gregor Tanner,et al.  Wireless power distributions in multi-cavity systems at high frequencies , 2020, Proceedings of the Royal Society A.

[8]  Yi Huang,et al.  Anechoic and Reverberation Chambers , 2018 .

[9]  Robert E. Richardson,et al.  Wireless Channel Modeling of Multiply Connected Reverberant Spaces: Application to Electromagnetic Compatibility Assessment , 2013, IEEE Transactions on Electromagnetic Compatibility.

[10]  R E Richardson,et al.  Reverberant Microwave Propagation in Coupled Complex Cavities , 2011, IEEE Transactions on Electromagnetic Compatibility.

[11]  E. Ott,et al.  Predicting the statistics of wave transport through chaotic cavities by the Random Coupling Model: a review and recent progress , 2013, 1303.6526.

[12]  Thomas M. Antonsen,et al.  Random Coupling Model for interconnected wireless environments , 2014, 2014 IEEE International Symposium on Electromagnetic Compatibility (EMC).

[13]  Troels Pedersen,et al.  An Iterative Transfer Matrix Computation Method for Propagation Graphs in Multiroom Environments , 2019, IEEE Antennas and Wireless Propagation Letters.

[14]  Larry J. Greenstein,et al.  Characterizing indoor wireless channels via ray tracing combined with stochastic modeling , 2009, IEEE Transactions on Wireless Communications.

[15]  R S Langley,et al.  A Reciprocity Approach for Computing the Response of Wiring Systems to Diffuse Electromagnetic Fields , 2010, IEEE Transactions on Electromagnetic Compatibility.

[16]  G. B. Tait,et al.  Wireless RF Energy Propagation in Multiply-Connected Reverberant Spaces , 2011, IEEE Antennas and Wireless Propagation Letters.

[17]  Edward Ott,et al.  Impedance and power fluctuations in linear chains of coupled wave chaotic cavities. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Extraction of the coupling impedance in overmoded cavities , 2019, Wave Motion.